Redeeming by Unlearning: A Critical Discourse Analysis of COVID ‐19 Vaccine Hesitancy on Facebook (original) (raw)
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Introduction: This study combines quantitative and qualitative analyses of social media data collected through three key stages of the pandemic, to highlight the following: • 'First wave' (March to May, 2020): negative consequences arising from a disconnect between official health communications, and unofficial Long Covid sufferers' narratives online. • 'Second wave' (October 2020 to January 2021): closing the 'gap' between official health communications and unofficial patient narratives, leading to a better integration between patient voice, research and services. • 'Vaccination phase' (January 2021, early stages of the vaccination programme in the UK): continuing and new emerging concerns. Methods: We adopted a mixed methods approach involving quantitative and qualitative analyses of 1.38 million posts mentioning long-term symptoms of Covid-19, gathered across social media and news platforms between 1 January 2020 and 1 January 2021, on Twitter, Facebook, Blogs, and Forums. Our inductive thematic analysis was informed by our discourse analysis of words, and sentiment analysis of hashtags and emojis. Results: Results indicate that the negative impacts arise mostly from conflicting definitions of Covid-19 and fears around the Covid-19 vaccine for Long Covid sufferers. Key areas of concern are: time/duration; symptoms/testing; emotional impact; lack of support and resources. Conclusions: Whilst Covid-19 is a global issue, specific sociocultural, political and economic contexts mean patients experience Long Covid at a localised level, needing appropriate localised responses. This can only happen if we build a knowledge base that begins with the patient, ultimately informing treatment and rehabilitation strategies for Long Covid.
Revista Latina de Comunicación Social, 2021
Introduction: The debate on the Covid-19 vaccines has been very present on social networks since the very beginning of the health crisis, in a context of infodemics in which the presence of all kinds of information has been a breeding ground for misinformation or false news. Methodology: In this context, this article seeks to measure and characterize the conversation about Covid-19 vaccines on the social network Twitter. To this end, 62,045 tweets and 258,843 retweets from supporters and opponents of the vaccine were analyzed between December 2020 and February 2021. Results: The start of the vaccination campaign was the turning point at which pro-vaccine discourse began to take precedence over anti-vaccine discourse. Antivaccine groups are characterized by being strongly cohesive clusters, with an appreciable level of activity, but with less capacity to viralize content. Conclusions and discussion: Anti-vaccine discourses tend to rely on alternative media or content shared on social networks, which corroborates that quality information is one of the main measures against disinformation. It also highlights the role of quality or legacy media and the desirability of further developing anti-disinformation policies specific to the type of digital conversation taking place on Twitter.